Characterization of Csy4 motifs through the construction of RNA-regulated genetic feedback and RNA stability systems

Characterization of Csy4 motifs
through the construction of RNAregulated genetic feedback and RNA
stability systems.
Gin (officially Raúl) García Martín
Supervisor: Ebbe Sloth Andersen
Aarhus University
December 2020
1
Abstract
Csy4 is an endoribonuclease of the Cas family that cleaves RNA and generates mature
CRISPR-derived RNAs. Its applications in RNA bionanotechnology have yet to be fully
explored. This project aims to characterize the binding and cleaving mechanism of the
Csy4 enzyme, as well as to find possible applications in synthetic biology, through two
separate experiments.
First, the stability of an RNA origami-based system which contains fluorescent aptamers
and Csy4 cleaving motifs will be analyzed in the presence of an active Csy4. What is
more, this rationally designed RNA assembly could incorporate new elements such as
aptamers or riboswitches, allowing for a sequential control of reactions. A possible
application for this is a kill-switch which could, for example, prevent genetically modified
microorganisms from propagating outside of the lab.
Second, the binding affinity of different Csy4 motifs to a deactivated Csy4 will be tested,
along with the design of a negative feedback loop. This experiment had to be cancelled,
due to the corona restrictions set in December. This loop’s behavior was expected to be
that of an oscillator; therefore, it could be used as an element for designing and regulating
logical circuits.
2
Index
Abstract ............................................................................................................................. 1
1 Preface ......................................................................................................................... 3
2 Introduction ................................................................................................................. 4
2.1 The structure of RNA ............................................................................................. 4
2.1.1 RNA secondary structure ................................................................................ 4
2.1.2 RNA tertiary structure ..................................................................................... 6
2.1.3 RNA quaternary structure ................................................................................ 6
2.2 RNA nanotechnology ............................................................................................. 6
2.2.1 RNA synthetic biology .................................................................................... 6
2.2.2 Aptamers .......................................................................................................... 7
2.2.3 Riboswitches.................................................................................................... 7
2.2.4 RNA origami ................................................................................................... 7
2.2.5 CRISPR and the Csy4 endoribonuclease ........................................................ 9
2.3 Objectives ........................................................................................................... 9
3 Methods ....................................................................................................................... 9
3.1 Technical description of methods used ................................................................... 9
3.1.1 PCR.................................................................................................................. 9
3.1.2 Nanodrop ....................................................................................................... 10
3.1.3 Flow cytometry .............................................................................................. 10
3.1.4 Computer-aided design .................................................................................. 11
3.1.5 Chemical synthesis of oligonucleotides ........................................................ 11
3.1.6 gBlocks .......................................................................................................... 11
3.1.7 Golden Gate assembly ................................................................................... 12
3.2 Experimental section ............................................................................................. 12
3.2.1 Kill-switch ..................................................................................................... 12
3.2.2 Negative feedback loop ................................................................................. 16
4 Results and discussion ............................................................................................... 19
4.1 Kill-switch ............................................................................................................ 19
4.2 Negative feedback loop ........................................................................................ 27
5 Conclusion ................................................................................................................. 30
6 References ................................................................................................................. 31
7 Supplementary material ............................................................................................. 33
3
1 Preface
This project wouldn’t have been possible without the help of the Andersen lab members.
The realization of this project is driven by my passion for Synthetic Biology. It is one of
my dreams to be able to truly apply the principles of engineering to biological systems,
walking on a landfill of endless opportunities. My wish is that all the potential that nature
hasn’t projected could be put to good use, and also give us insight and reflections on the
origin and evolution of life, as well as the role we should play on it.
Taking this into account, Ebbe Sloth Andersen kindly introduced me to two of his team
members, George and Michael. All together, they guided me and helped me choose a
topic that would fit my passion, as well as the lab’s research lines.
That is how we decided to follow up on one of Michael’s experiments. Michael had been
working with the enzyme Csy4, and noticed there were difficulties when trying to
measure its binding affinity to several motifs. Then he suggested we could construct a
negative feedback loop, where we could at the same time test for different binding
affinities. What is more, we decided to build RNA origamis containing Csy4 motifs, and
quantify and analyze their digestion when co-expressed with the Csy4.
However, the multi-gene assemblies for the negative feedback loop were unsuccessful,
and, due to the new corona restrictions, I lacked of the opportunity to redo or reframe the
experiment further. Still, I was able to gather valuable data, which will be shown
throughout the report.
First of all, I would like to thank Ebbe for accepting my Individual Project, welcoming
me into his lab and building an inclusive atmosphere, which is something very important
to me. I would like to enormously thank George for patiently and correctly guiding me
through each step. I want to thank Michael for his disposition and help. Thanks to Cody
for letting me use his software. And thanks to Néstor, Bente and the rest of the team for
making the lab a cozy place to work in.
4
2 Introduction
2.1 The structure of RNA
Ribonucleic acids (RNA) are negatively charged polymers assembled from four different
monomers. Each monomer is composed of one of the four standard nucleic acid bases
(the pyrimidines uracil and cytosine, and the purines guanine and adenine) attached to a
conserved phosphorylated sugar (Westhof & Auffinger, 2000). The primary structure
of RNA is the sequence of bases attached to the sugar–phosphate backbone.
In salty water, the RNA molecules fold via Watson–Crick base pairing between the bases
(A with U, G with C or U) leading to double-stranded helices interrupted by singlestranded regions in internal loops or hairpin loops (Westhof & Auffinger, 2000). The
enumeration of the base-paired regions or helices constitutes a description of the
secondary structure of RNA.
Under appropriate conditions, structured RNA molecules undergo a transition to a 3D
fold, where the helices and the unpaired regions are precisely organized in space. This is
called the tertiary structure of RNA. This folding process usually depends on the
presence of divalent ions like magnesium ions and on the temperature (Westhof &
Auffinger, 2000).
The final structure level is the quaternary structure, where separate RNA molecules
interact with each other or with proteins.
2.1.1 RNA secondary structure
RNA secondary structure is the base-pairing interactions within a single ribonucleic acid
polymer, or between two polymers. It can be represented as a list of paired bases. The
secondary structures of biological RNA is single-stranded and often forms complex and
intricate base-pairing interactions. This occurs due to the fact that RNA has an extra
hydroxyl group in the ribose sugar, which increases its ability to form hydrogen bonds
(Dirks, Lin, Winfree, & Pierce, 2004).
Stem-loop structures
The secondary structure of nucleic acid molecules can be often decomposed into stems
and loops. The stem-loop structure (also often referred to as a "hairpin"), where a basepaired helix ends in a short unpaired loop, is extremely common and is a building block
for larger structural motifs such as cloverleaf structures, four-helix junctions like those
found in transfer RNA (Svoboda & Di Cara, 2006).
Internal loops (a short series of unpaired bases in a longer paired helix) and bulges
(regions where one strand of a helix has "extra" inserted bases with no counterparts in the
opposite strand) are also frequent. See Figure 1 for an overview of the main elements of
the stem-loops.
5
Figure 1. RNA stem-loops. (a) A schematic overview of an RNA stem-loop depicting the important
parameters for the role of such a hairpin RNA. Extracted from (Svoboda & Di Cara, 2006).
There are many secondary structure elements of functional importance to biological
RNAs; some famous examples are the Rho-independent terminator stem-loops and the
tRNA cloverleaf.
Pseudoknots
A pseudoknot is a nucleic acid secondary structure containing at least two stem-loop
structures in which half of one stem is intercalated between the two halves of another
stem (Figure 2). Pseudoknots fold into knot-shaped three-dimensional conformations but
are not true topological knots.
Figure 2. An example of the RNA pseudoknot structure, from the human telomerase. Adapted from
(J. L. Chen & Greider, 2005).
The base pairing in pseudoknots is not well nested; that is, base pairs occur that "overlap"
one another in sequence position. This makes the presence of general pseudoknots in
nucleic acid sequences impossible to predict by the standard method of dynamic
programming, which uses a recursive scoring system to identify paired stems and
consequently cannot detect non-nested base pairs.
However, limited subclasses of pseudoknots can be predicted using modified dynamic
programs (Rivas & Eddy, 1999).
6
2.1.2 RNA tertiary structure
Nucleic acid tertiary structure is the three-dimensional shape of a nucleic acid polymer.
RNA and DNA molecules are capable of diverse functions ranging from molecular
recognition to catalysis. Such functions require a precise three-dimensional tertiary
structure. While such structures are diverse and seemingly complex, they are composed
of recurring, easily recognizable tertiary structure motifs that serve as molecular building
blocks.
Double helix
The double helix is an important tertiary structure in nucleic acid molecules which is
intimately connected with the molecule's secondary structure. A double helix is formed
by regions of many consecutive base pairs.
The nucleic acid double helix is a spiral polymer, usually right-handed, containing two
nucleotide strands which base pair together. A single turn of the helix constitutes about
ten nucleotides, and contains a major groove and minor groove, the major groove being
wider than the minor groove (Soediono, 1989).
2.1.3 RNA quaternary structure
Nucleic acid quaternary structure refers to the interactions between separate nucleic acid
molecules, as well as between nucleic acid molecules and proteins. This concept is an
analogy to protein quaternary structure, so it hasn’t been highly specified (Jones & FerréD’Amaré, 2015). An example of RNA quaternary structure would be the ribosome, where
different RNA monomers interact with each other and with proteins.
2.2 RNA nanotechnology
2.2.1 RNA synthetic biology
Synthetic biology is a set of tools for biology that is based on principles such as
abstraction, standardization and automated construction in order to modify and create new
biological systems.
Most synthetic biology efforts so far have focused on engineering gene circuits that rely
on protein-DNA interactions. Recent advances in RNA biology and nucleic acid
engineering, however, are inspiring the use of RNA components in the construction of
synthetic biological systems (Isaacs, Dwyer, & Collins, 2006).
Indeed, structural motifs in naturally occurring RNAs and RNPs can be employed as new
molecular parts for synthetic biology to facilitate the development of novel devices and
systems that modulate cellular functions. For instance, functional RNA molecules such
as new artificial RNA aptamers and RNA enzymes (ribozymes) can be used to reprogram
existing gene regulatory systems (Saito & Inoue, 2009). Another option is to directly used
small RNAs as transcriptional activators by preventing the formation of terminator
hairpins (Chappell, Takahashi, & Lucks, 2015).
7
2.2.2 Aptamers
Aptamers are oligonucleotide or peptide molecules that bind to a specific target molecule.
They are generally created by selecting them from a large random sequence pool (by
“Systematic Evolution of Ligands by EXponential enrichment”, or SELEX), but natural
aptamers also exist in riboswitches.
Aptamers can be used for both basic research and clinical purposes as macromolecular
drugs. Aptamers can be combined with ribozymes to self-cleave in the presence of their
target molecule (Mallikaratchy, 2017).
2.2.3 Riboswitches
Riboswitches are a type of mRNA structure that help regulate gene expression and often
bind a diverse set of ligands. Riboswitches determine how gene expression responds to
varying concentrations of small molecules in the cell (Figure 3) (Y. Chen & Varani,
2010). This motif has been observed in flavin mononucleotide (FMN), cyclic di-AMP (cdi-AMP), and glycine.
Riboswitches are said to show pseudoquaternary structure: several structurally similar
regions of a single RNA molecule fold together symmetrically. Because this structure
arises from a single molecule and not from multiple separate molecules, it cannot be
referred to as true quaternary structure (Jones & Ferré-D’Amaré, 2015). Depending on
where a riboswitch binds and how it is arranged, it can, for example, suppress or allow a
gene to be expressed (Y. Chen & Varani, 2010).
Figure 3. A synthetic theophylline-responsive riboswitch variant adopts a fold that sequesters the
ribosome binding site (RBS) in the mRNA transcript. In the presence of the substrate, theophylline,
the riboswitch adopts a conformation where the aptamer is bound to theophylline. The RBS is then
released and protein translation can take place. Extracted from (Seeliger et al., 2012).
2.2.4 RNA origami
Self-folding of an information carrying polymer into a compact particle with defined
structure not only is a foundation of biology but it also offers attractive potential as a
synthetic strategy.
Over the past three decades, nucleic acids have been used to create a variety of complex
nanoscale shapes and devices. RNA offers unique application potentials over DNA
8
structures, such as functional diversity, economical production via genetic expression,
and amenability for intracellular applications.
RNA origami is synthesized by enzymes that fold RNA into particular shapes (in vivo).
This method was developed by researchers from Aarhus University and California
Institute of Technology (C. W. Geary & Andersen, 2014). Even though many computer
algorithms are present to help with RNA folding, none can fully predict the folding of
RNA of a singular sequence (C. W. Geary & Andersen, 2014).
Computer-aided design
Computer-aided design of the RNA origami structure is divided into three main steps;
creating the 3D model, writing the 2D structure, and designing the sequence.
First, a 3D model is constructed using tertiary motifs from existing databases. This is
necessary to ensure the created structure has feasible geometry and strain. Next, the 2D
structure is created by describing the strand path and base pairs from the 3D model. This
2D blueprint introduces sequence constraints, creating primary, secondary and tertiary
motifs. Last, sequences compatible with the desired structure are designed. For this
purpose, design algorithms can be used (Sparvath, Geary, & Andersen, 2017).
The double crossover (DX)
The RNA origami method uses double-crossovers (DX) to arrange the RNA helices in
parallel to each other to form building blocks. While DNA origami requires the
construction of DNA molecules from multiple strands, the DX molecules can be made
from only one strand for RNA, by adding hairpin motifs to the edges and kissing-loop
complexes on the internal helices (see Figure 4). The addition of more DNA molecules
on top of one another creates a junction known as the dovetail seam. This dovetail seam
has base pairs that cross between adjacent junctions; thus, the structural seam along the
junction is sequence-specific (Sparvath et al., 2017).
Figure 4. Design of DNA origami. The main RNA strand is shown in black, while the colored strands
are kissing loop complexes (4-T loop, see structure inside the black box). The kissing loops can
cross the dovetail seem and stabilize it. Extracted and adapted from (Rothemund, 2006).
9
2.2.5 CRISPR and the Csy4 endoribonuclease
The CRIPSR-Cas system is a bacteria and archaea adaptive immune systems that relies
on small RNAs for defense against invasive genetic elements. CRISPR (clustered
regularly interspaced short palindromic repeats) genomic loci are transcribed as long
precursor RNAs, which must be enzymatically cleaved to generate mature CRISPRderived RNAs (crRNAs) that serve as guides for foreign nucleic acid targeting and
degradation (cleavage by a Cas family enzyme).
This processing occurs within the repetitive sequence and is catalyzed by a dedicated
Cas6 family member in many CRISPR systems. In Pseudomonas aeruginosa, crRNA
biogenesis requires the endoribonuclease Csy4, which recognizes its RNA substrate via
sequence- and structure-specific contacts and cleaves them at the 3’ end of a five-basepair stem-loop encoded by the CRISPR repeat. RNA cleavage by Csy4 is divalent metal
ion-independent and requires chemical activation of a ribosyl 2’-hydroxyl for internal
nucleophilic attack on the phosphodiester bond. (Sternberg, Haurwitz, & Doudna, 2012).
2.3 Objectives
1. Characterization of the binding and cleaving mechanism of the Csy4
endoribonuclease.
2. Analysis of the stability of an RNA origami-based system in the presence of Csy4.
The design contains fluorescent aptamers and Csy4 cleaving motifs. The eventual
objective is the design of a kill-switch.
3. Characterization of the binding affinity of dCsy4 to different Csy4 RNA motifs
for the design of a negative feedback loop, which can regulate logical circuits.
3 Methods
3.1 Technical description of employed methods
3.1.1 PCR
Polymerase Chain Reaction (PCR) is an enzymatic process where specific regions of
DNA are duplicated repeatedly to yield millions of copies of a particular sequence in a
matter of few hours. It involves repeated cycles of heating and cooling of a reaction
mixture containing DNA template, DNA polymerase, primers, and nucleotides, being the
DNA template the one containing the target sequence.
Primers are short chains of nucleotides which locate the specific target DNA of interest
and bind to it upon cooling, through complementary base pairing. They act as a starting
point for DNA polymerase to create the new complementary strand. DNA polymerase is
an enzyme that synthesizes new strands of DNA complementary to the target sequence
(Jalali, Zaborowska, & Jalali, 2017).
Each cycle of PCR consists of three steps (Jalali, Zaborowska, & Jalali, 2017):
•
Denaturation. The reaction mixture is heated to over 90˚C to unwind the double
helix by breaking apart hydrogen bonds.
10
•
•
Primer annealing. The reaction mixture is cooled to 45-65˚C to allow for primer
annealing. Forward and reverse primers hybridize through complementary base
pairing to opposite strands of the DNA.
Extension. The reaction mixture is heated to 72˚C toward the optimal temperature
or DNA polymerase enzyme activity. The DNA polymerase then binds to the
primer-template hybrid complex and assembles a new complementary strand
using the free nucleotides in the reaction mixture. After extension, the cycle is
restarted.
The PCR method used for this project involved using the Q5® High-Fidelity DNA
Polymerase (NewEngland BioLabs INC., Ipswich, MA). Next, the Macherey-Nagel
Inc.’s PCR clean-up and DNA purification kit and protocol were followed.
The PCR clean-up is preceded and complemented by the treatment of PCR product DNA
with DpnI (methylation-sensitive restriction enzyme). Plasmids propagated into
Escherichia coli are methylated and thus cut by DpnI. This is done to minimize wrong
clones by eliminating the DNA not produced by the PCR.
3.1.2 Nanodrop
The NanoDrop® microvolume sample retention system (Thermo Scientific NanoDrop
Products) is a high-sensitivity fluorescent analysis of limited mass. It functions by
combining fiber optic technology and natural surface tension properties to capture and
retain minute amounts of sample independent of traditional containment apparatus such
as cuvettes or capillaries.
Different molecules absorb different wavelengths of light. DNA happens to absorb light
at the wavelength of 260nm, proteins at 280nm and other contaminants at around 230.
The NanoDrop® shines light of those different wavelengths through the sample and
records how much light got absorbed. It then uses a built-in equation to convent
absorption at 260nm into a DNA concentration. These ratios give a rough idea of how
pure the sample is, and what types of contaminants might be present.
3.1.3 Flow cytometry
Flow cytometry is a sophisticated instrument that can measure the optical and
fluorescence characteristics of a single cell or another particle in a fluid stream when they
pass through a light source. Antibodies or dyes can be used to detect several parameters
such as size, granularity and fluorescence (Adan, Alizada, Kiraz, Baran, & Nalbant, 2017).
The principles behind flow cytometry are light scattering and fluorescence emission,
which occurs when light from the excitation source hits the moving particles. Light
scattering is directly related to structural and morphological properties of the cell while
fluorescence emission is proportional to the amount of fluorescent probe bound to the cell
or cellular component (Adan et al., 2017). The fluorescence is shown in A.U. (arbitrary
units), since absolute quantification can’t be performed without standards.
11
3.1.4 Computer-aided design
ViennaRNA Package
The ViennaRNA Package consists of a C code library and several stand-alone programs
for the prediction and comparison of RNA secondary structures (Lorenz et al., 2011).
The main secondary structure prediction tool is RNAfold, which uses a set of
thermodynamic energy parameters to compute the minimum free energy (MFE) and
back-traces an optimal secondary structure. The minimum free energy structure of a
sequence is the secondary structure that is calculated to have the lowest value of free
energy.
NUPACK: Nucleic Acid Package
NUPACK is a software suite for the analysis and design of nucleic acid structures, devices,
and systems.
The NUPACK web application enables analysis and design of the equilibrium basepairing properties of one or more test tubes of interacting nucleic acid strands (Zadeh et
al., 2011). Among others, it can calculate the partition function and minimum free energy
(MFE) secondary structure for pseudoknot-free complexes of arbitrary numbers of
interacting RNA or DNA strands.
NUPACK was used to analyze the folding of the different suboptimal structures obtained
with Cody Geary’s RNA design software (Geary et al., 2021) rendered. The structures
with the lowest free-energy were selected.
KineFold
The Kinefold web server provides a web interface to simulate nucleic acid folding paths
at the level of nucleation and dissociation of RNA/DNA helix regions (Xayaphoummine,
Bucher, & Isambert, 2005). The folding path consists of a discrete series of secondary
structures obtained by the successive addition or removal of single helices.
An advantage to KineFold is that both pseudoknots and knots are efficiently predicted, as
simple geometrical and topological constraints are taken into account. If the simulated
molecular time is long enough, a stochastic (randomly determined) simulation like
KineFold will eventually find the lowest free energy structures.
KineFold was used together with NUPACK to determine and select the lowest freeenergy structures obtained with Cody Geary’s RNA design software.
3.1.5 Chemical synthesis of oligonucleotides
This chemical synthesis of oligonucleotides was performed by Integrated DNA
Technologies Inc. (IDT).
3.1.6 gBlocks
gBlocks Gene Fragments are double-stranded DNA fragments 125–3000 bp in length
with a median error rate of less than 1:5000. They are synthesized by Integrated DNA
Technologies Inc (IDT).
12
Each gBlocks Gene Fragment goes through a quality control process, which includes size
verification by capillary electrophoresis and sequence identification by mass
spectrometry. The advantage relies on the fact that each this rigorous testing ensures that
most recombinant colonies obtained from cloning each gBlocks Gene Fragment will
contain the desired insert.
3.1.7 Golden Gate assembly
Golden Gate cloning or Golden Gate assembly is a molecular cloning method that allows
the simultaneous and directional assembly of multiple DNA fragments. The enzymes
used are the T4 DNA ligase as well as Type IIs restriction enzymes, such as BsaI or
BsmBI.
This kind of Type II restriction enzymes have the ability to cut DNA outside of their
cleavage motifs and, therefore, can create non-palindromic overhangs. Since more than
200 potential overhang sequences are possible, multiple fragments of DNA can be
assembled by using combinations of overhang sequences. In practice, this means that
Golden Gate cloning is typically scarless. Apart from that, since the assembled product
does not have a Type II restriction enzyme cleaving motif, it cannot be cut again, so the
reaction is irreversible (Weber, Engler, Gruetzner, Werner, & Marillonnet, 2011).
In this project, we followed two different Golden Gate protocols: one for part assemblies
and another one for multiple assemblies (both for cassette and multi-gene cassette
assemblies). They can be found under the “Supplementary material” section.
3.2 Experimental section
3.2.1 Kill-switch
3.2.1.1 Design of RNA origami tiles
Five different RNA origami tiles were designed using the 2H-AE as a starting point
(Figure 5). This tile was constructed by Geary et al. (C. Geary, Rothemund, & Andersen,
2014). The DNA constructs, as well as their primers, were designed and assembled in the
Benchling™ web tool.
Figure 5. 2D blueprint of the 2H-AE tile. Both the 5’ and 3’ ends can be seen in the last (lower) line,
since it is a single-stranded (ss) RNA origami tile. Nucleotides depicted as “N” are unspecified. A
special software is used to select them and generate different variants, usually based on
parameters such as the minimum free energy (MFE).
13
The 2D blueprint of this tile was modified by using the Sublime Text text editor. The first
common modification for all designs consisted of adding the iSpinach aptamer on the
upper left cornering sequence.
First, the base tile was created by adding the sequences of the Csy4 motif in the three
selected corners (Figure 6a).
Figure 6. 2D blueprint of the RNA origami tile designs. (A) 2H_iSPI_0CSY4 tile, containing only
the iSpinach aptamer (sequence highlighted in pink). The three corners for Csy4 motif insertion are
numbered from 1 to 3 (white numbers). (B) 2H_iSPI_3CSY4 tile, containing both the iSpinach
aptamer and the Csy4 motifs inserted simultaneously in the three possible corners.
For this project, ViennaRNA’s secondary structure prediction through energy
minimization function was used along with Cody Geary’s RNA design software
(Sparvath et al., 2017) to generate suboptimal structures within a given energy range of
the optimal energy of the base tile. Thirty different models for the targeted RNA origami
tile were obtained.
From them, we selected those with the lowest MFE, and analyzed them once more using
NUPACK and KineFold. This process was designed in order to select the structure that
rendered the lowest MFE in consensus with the three pieces of software, as they employ
different methods for calculating this parameter.
This rendered the structure shown in Figure 6b, and using this one as a starting point,
four other tiles were generated:
•
•
•
•
•
2H_iSPI_0CSY4, or M0 for short, no Csy4 motifs.
2H_iSPI_3CSY4, Csy4 motifs on the three corners.
2H_iSPI_CSY4_1, or M1, Csy4 motif on corner position number 1 (Figure 6a).
2H_iSPI_CSY4_2, or M2, Csy4 motif on corner position number 2.
2H_iSPI_CSY4_3, or M3, Csy4 motif on corner position number 3.
14
3.2.2.2 Synthesis of RNA structures
1. Sequence synthesis
The five designed DNA sequences were ordered from Integrated DNA Technologies Inc.
They were synthesized by using the chemical synthesis of oligonucleotides with the
phosphoramidite approach.
They were amplified in a thermocycler by PCR, which used primers that targeted our
designed sequences and also added the prefixes and suffixes later needed for the Golden
Gate assembly.
2. Part assembly
For the part assembly, the five different PCR products were assembled into an entry
vector, pECO85. The method used was the Golden Gate, and five PCR tubes with the
mixture specified by the protocol were inserted in the thermocycler and the Golden Gate
protocol was run (see “Supplementary material”).
3. Cassette assembly
A Golden Gate assembly of the cassettes was performed, using BsaI as the Type II
restriction enzyme. Six PCR tubes (one for each RNA cassette design plus the protein
cassette) composed of the elements shown in Table 1 were inserted in the thermocycler
and the Golden Gate protocol was run (see “Supplementary material”).
Table 1. Components for the cassette assembly of the Kill-switch. “Dest. Vector” stands for
“Destination Vector” and it’s the plasmid that will act as the backbone of the assembly, which
confers resistance to carbenicillin and also carriers a marker: pECO79, mCherry and pECO83,
mVenus. There are two different constructs: the RNA cassette and the Protein cassette. For the
RNA cassette, five different RNA cassettes were formed, as the P3 column is variable and consists
of the part assembly of each of the tiles. Its P1 and P4 contain the promoter and terminator
sequences, respectively. For the protein cassette, just one assembly was formed, as it matches all
five RNA cassettes. Its columns contain DNA sequences for: P1, promoter; P2, ribosome binding
site; P3, chloramphenicol resistance; P4; Csy4 and P5, terminator.
Next, NEB® Turbo Competent E. coli (High Efficiency) cells were transformed with
these constructs. In order to do so, 40 microliters of Turbo® cells were added to each of
the PCR tubes containing the assemblies and the transformation protocol of the company
was run on the thermocycler. Once finished, 150 microliters of SOC media were added
to each tube and incubated in the incubator at 37 ºC and 225 rpm for one hour.
The strains were then plated and selected on carbenicillin plates. They were left to grow
overnight. Next, one colony from each design was piqued and liquid cultured in falcon
tubes (5 ml LB media and 5 microliter of chloramphenicol). They were incubated
overnight at 37 ºC and 225 rpm.
One day after, the plasmid DNA was purified (Macherey-Nagel Inc.’s kit and protocol)
and sent for sequencing.
15
IDT’s sequencing service confirmed the correct assembly of four of the designs. However,
it was noticed that the RNA origami tile with Csy4 motifs in all three corners,
2H_iSPI_3CSY4, rendered an incorrect cassette assembly. The experiment was repeated
for this construct, but the assembly was incorrect yet again. Therefore, the experiments
proceeded forward without this design.
4. Multi-gene cassette assembly
A Golden Gate multi-gene assembly of the cassettes was performed, using Esp3I as the
Type II restriction enzyme and pECO84 as the backbone. pECO84 contains the IPTGinducible standard promoter J23100. Four PCR tubes with the specified mixture (Table
2) were inserted in the thermocycler and the Golden Gate protocol was run (see
“Supplementary material”).
Table 2. Components for the multi-gene cassette assembly of the Kill-switch. “Dest. Vector” stands
for “Destination Vector” and it’s the plasmid that will act as the backbone of the assembly, which
confers resistance to chloramphenicol and also carriers a marker: pECO84, mVenus. The rest of
the columns (P1-2) are the DNA sequences, inserts, assembled into the backbone. The P1 element
is variable and consists of the cassette assembly of each of the tiles. The P2 element, the protein
cassette, is the same for all the cassettes.
Next, NEB® Turbo Competent E. coli (High Efficiency) cells were transformed with
these constructs. In order to do so, 40 microliters of Turbo® cells were added to each of
the PCR tubes containing the assemblies and the transformation protocol of the company
was run on the thermocycler. Once finished, 150 microliters of SOC media were added
to each tube and incubated in the incubator at 37ºC and 225 rpm for one hour.
The strains were then plated and selected on chloramphenicol plates. They were left to
grow overnight. Next, one colony from each design was piqued and liquid cultured in
falcon tubes (5ml LB media and 5 microliters of chloramphenicol). They were incubated
overnight at 37ºC and 225 rpm.
One day after, the plasmid DNA was purified (Macherey-Nagel Inc.’s kit and protocol)
and sent for sequencing. IDT’s sequencing service confirmed the correct assembly of the
four designs.
Then, JM109(DE3) cells were transformed with these constructs. In order to do so, 40
microliters of JM cells were added to each of the PCR tubes containing the assemblies
and the transformation protocol of the company was run on the thermocycler. Once
finished, 150 microliters of SOC media were added to each tube and incubated in the
incubator at 37 ºC and 225 rpm for one hour. The strains were then plated and selected
on chloramphenicol plates. They were left to grow overnight.
5. Flow cytometry
First, each well of the first two rows of a 72-well plate was filled with 300 microliters of
LB media and 0.3 microliters of chloramphenicol (pipetted from a master mix of 10 ml
LB and 10 microliters of chloramphenicol).
16
Three colonies were piqued from the plates of each design and placed each in a well of
the first row. A membrane was fixed over the plate, allowing oxygen to pass through, but
preventing contamination. The plate was incubated in the heat block overnight at 37 ºC
and 900 rpm.
Next day, 6 microliters from each well in the first row were added to their respective wells
in the second row (both wells, donor and acceptor, sharing the same column). The plate
was left to incubate in the heat block for 2 hours at 37 ºC and 900 rpm. Next, half of the
second row’s liquid content was transferred to the third row. To both second and third
row, the iSpinach’s fluorophore was added, DFHBI (10 μM final concentration), and to
the third row only, 0.3 microliters of IPTG (1 M) were added in each well, in order to
induce the expression of the constructs. Again, the plate was left to incubate in the heat
block this time for 4 hours at 37 ºC and 900 rpm.
Afterwards, the flow cytometry was performed, and the fluorescent emission data was
recorded.
3.2.2 Negative feedback loop
3.2.2.1 Design of RNA constructs
Five different RNA constructs for cell transformation were designed following the
sequence structure showcased in Figure 7. The Csy4 binding motifs were designed after
those that Sternberg et al. employed in order to analyze the binding affinities of dCsy4 to
several modified motifs (Figure 8) (Sternberg et al., 2012).
The RNA constructs, as well as the primers for mutation and amplification, were designed
and assembled in the Benchling™ web tool.
Figure 7. Schematic representation of the RNA constructs’ elements and the mechanism behind
the negative feedback loop. From left to right in the DNA scheme (bottom): black arrow, IPTG
inducible promoter; brown half-circle, pET3a ribosome binding site (RBS); AUG box, AUG start
codon; pink stem-loop, one of the five different stem-loop designs for the Csy4 motif; colored arrow,
gene for the deactivated Csy4 (dCsy4); black T, terminator. After transcription, the mRNA of the
dCsy4 can follow two routes. First, it can be translated into dCsy4. Second, the already existing
dCsy4 can bind to its motif (in the mRNA), thus blocking the translation of more dCsy4, and
generating a negative feedback loop.
17
Figure 8. Csy4 binding motifs used in the design of the negative feedback loop. Extracted and
adapted from (Sternberg et al., 2012).
3.2.2.2 Synthesis of RNA structures
1. Sequence synthesis
The five designed DNA sequences were ordered from Integrated DNA Technologies Inc.
They were synthesized by using the chemical synthesis of oligonucleotides with the
phosphoramidite approach.
The plasmid pBP120 was used as a template and the designed primers were used to mutate
(add the specific Csy4 motif for each design) and amplify the DNA construct. They were
amplified in a thermocycler by PCR, which used primers that targeted our designed
sequences and also added the prefixes and suffixes later needed for the Golden Gate
assembly.
2. Part assembly
For the part assembly, the five different PCR products were assembled into an entry
vector, pECO83. The method used was the Golden Gate, and five PCR tubes with the
mixture specified by the protocol were inserted in the thermocycler and the Golden Gate
protocol was run (see “Supplementary material”).
3. Cassette assembly
A Golden Gate assembly of the cassettes was performed, using BsaI as the Type II
restriction enzyme. Five PCR tubes with the specified mixture (Table 3) were inserted in
the thermocycler and the Golden Gate protocol was run (see “Supplementary material”).
Table 3. Components for the cassette assembly of the Negative feedback loop. “Dest. Vector”
stands for “Destination Vector” and it’s the plasmid that will act as the backbone of the assembly,
which confers resistance to carbenicillin and also carriers a marker. For the pECO83, this marker
is mVenus. The rest of the columns (P1-5) are the DNA sequences, which contain: P1, promoter;
P2, Chloramphenicol resistance; P3, dCsy4 and P4, terminator. The P2 column is variable and
consists of the ribosome binding site together with the part assembly of each of the DNA constructs
with a different Csy4 motif.
Next, NEB® Turbo Competent E. coli (High Efficiency) cells were transformed with
these constructs. In order to do so, 40 microliters of Turbo® cells were added to each of
18
the PCR tubes containing the assemblies and the transformation protocol of the company
was run on the thermocycler. Once finished, 150 microliters of SOC media were added
to each tube and incubated in the incubator at 37ºC and 225 rpm for one hour.
The strains were then plated and selected on carbenicillin plates. They were left to grow
overnight. Next, one colony from each design was piqued and liquid cultured in falcon
tubes (5ml LB media and 5 microliter of chloramphenicol). They were incubated
overnight at 37ºC and 225 rpm.
One day after, the plasmid DNA was purified (Macherey-Nagel Inc.’s kit and protocol)
and sent for sequencing. IDT’s sequencing service confirmed the incorrect assembly of 5
of the designs. The cassette assembly was repeated following the same procedure, yet the
results were still unsatisfactory. Therefore, we made use of the gBlock Gene Fragment
service from Integrated DNA Technologies Inc. to generate the initial mRNA parts. Then,
rerunning the experiment generated the cassette assembly with the correct sequence.
4. Multi-gene cassette assembly
A Golden Gate multi-gene assembly of the cassettes was performed, using Esp3I as the
Type II restriction enzyme and pECO84 as the backbone. pECO84 contains the IPTGinducible standard promoter J23100. Five PCR tubes with the specified mixture (Table
4) were inserted in the thermocycler and the Golden Gate protocol was run (see
“Supplementary material”).
Table 4. Components for the multi-gene cassette assembly of the Kill-switch. “Dest. Vector” stands
for “Destination Vector” and it’s the plasmid that will act as the backbone of the assembly, which
confers resistance to chloramphenicol and also carriers a marker: pECO84, mVenus. The rest of
the columns (P1-2) are the DNA sequences, inserts, assembled into the backbone. The P1 element
is constant and consists of the pMN318 plasmid, which contains the dCsy4 protein cassette. The
P2 element is variable and consists of the cassette assembly of each of the tiles.
Next, NEB® Turbo Competent Escherichia coli (High Efficiency) cells were transformed
with these constructs. In order to do so, 40 microliters of Turbo® cells were added to each
of the PCR tubes containing the assemblies and the transformation protocol of the
company was run on the thermocycler. Once finished, 150 microliters of SOC media were
added to each tube and incubated in the incubator at 37ºC and 225 rpm for one hour.
The strains were then plated and selected on chloramphenicol plates. They were left to
grow overnight. Next, one colony from each design was piqued and liquid cultured in
falcon tubes (5ml LB media and 5 microliters of chloramphenicol). They were incubated
overnight at 37ºC and 225 rpm.
One day after, the plasmid DNA was purified (Macherey-Nagel Inc.’s kit and protocol)
and sent for sequencing. IDT’s sequencing service showed the incorrect assembly of the
five designs. Due to the corona restrictions, this part of the experiment was ended here.
19
4 Results and discussion
4.1 Kill-switch
The expression level of the Csy4 was measured with the help of mScarlet-I-H, a small
red fluorescent protein co-expressed with the enzyme. Seemingly, the expression and
correct folding of the RNA origami was measured with the iSpinach-H aptamer (inserted
in the origami), which binds to the DFHBI green fluorescence molecule.
Based on our initial hypothesis, the mScarlet-I-H fluorescence, that is, the Csy4
expression should be equal for all the constructs in the induced and uninduced
experiments, respectively. This is because its expression only depends on the promoter
and its strength, and this was common for all constructs.
From the data shown in Figure 9 and Table 5, we conclude that the ratios of Csy4
expression between the induced and uninduced samples were significant in all the
constructs, therefore the inducible promoter worked appropriately.
Figure 9. mScarlet-I-H fluorescence arbitrary values (A.U.) obtained in the flow cytometry. The
results for the four different tile designs are displayed as a mean of the three colonies each
construct had. For each, the blue bar on the left corresponds to the uninduced sample while the
orange bar on the right corresponds to the sample induced with IPTG. See original in
Supplementary material, Figure S2.
However, a clear difference can be spotted between the uninduced expression of M0 and
M1 versus the one of M2 and M3, being the former one much higher (Figure 9).
Regarding the induced expression, an increasing trend can be deduced, being M0 the
sample with the lowest expression, then M1, followed by M2 and finally M3, with the
highest expression value. These events are most surprising, since the induced and
uninduced mScarlet-I-H fluorescence values among groups were expected to be equal.
First, the unsuccessful constitutive expression specific to the M0 and M1 samples is
hypothesized to have been caused by errors during the DNA construct assembly process.
Therefore, when extracting conclusions, a uniform and constant distribution of uninduced
20
expression will be assumed for the four constructs. Second, this experimental error has
also affected the mScarlet-I-H ratios in Table 5, which will be assumed to have grown
linearly from M0 to M3.
Table 5. Ratios by construct and fluorescence type of induced (numerator) and uninduced
(denominator) samples.
Now, in order to explain the fluorescence differences among induced groups, a new
theory was hypothesized. It is thought that some RNA origamis misfolded, forming
aggregates that compromised cell viability, thus reducing the amount of fluorescence of
the cell population. This effect was not appreciated in the uninduced groups, due to a
lower expression yield of the RNA origamis.
Thus, M3 is speculated to show the expected red fluorescence value for the induced
groups (very little or null cellular burden), so its construct is the one showing the best
folding, closely followed by M2. On the contrary, M0 and M1 would show clear effects
of aggregation.
Since all the constructs share most of the components, including the inducible promoter,
and the construct-specific sequences are of similar length, the differences in folding could
be mainly accounted for the different spatial positioning of the Csy4 binding motifs inside
the RNA origami.
To analyze this effect, we will integrate this data with the measurements of the iSpinach
flow cytometry (Figure 10), since this is an indicator of the Csy4 cleaving activity, which
could potentially play an important role in preventing aggregation. This is because, once
cleaved, the RNA origami is likely to be degraded and cause no harm, nor accumulate.
iSpinach-H is the aptamer that binds and allows DFHBI to emit green fluorescence. The
iSpinach-H motif is shared by all the constructs. Basically, when the RNA origami is
intact, the aptamer can bind to DFHBI and allow it to emit green fluorescence. As the
origami is cleaved by Csy4 and degraded, the green fluorescence is expected to decrease.
From the data shown in Figure 10, we conclude that the ratios of the RNA origami
expression between the induced and uninduced samples was significant, therefore the
inducible promoter worked appropriately. A uniform and constant distribution of
uninduced expression can also be observed along the four constructs.
21
Figure 10. iSpinach-H fluorescence arbitrary values (A.U.) obtained in the flow cytometry. The
results for the four different tile designs are displayed as a mean of the three colonies each
construct had. For each, the blue bar on the left corresponds to the uninduced sample while the
orange bar on the right corresponds to the sample induced with IPTG. See original in
Supplementary material, Figure S3.
With regards to the induced RNA origami expression and correct folding (Figure 10), an
increasing trend can be deduced, being M0 the sample with the lowest expression, then
M1, followed by M2 and finally M3. It is remarkable that this trend is highly similar to
the one mScarlet-I-H showed in Figure 9.
Integrating the data from Figure 9 and Figure 10, it is believed that the reason why they
both follow a similar trend could be explained by fluorescent leakage. More specifically,
looking at the relative fluorescent values, those of mScarlet-I-H are significantly bigger
than those of iSpinach-H. Therefore, it was hypothesized that in Figure 10, it is actually
the leakage of the mScarlet-I-H red fluorescence that plays a major role in determining
the green fluorescence seen in each sample.
In order to support that hypothesis, an analysis of the excitation and emission ranges and
values of both fluorescent molecules was performed (Figure 11). Focusing on the green
fluorescence detection value (X abs), there is indeed a possibility that the fluorescence
emitted by mScarlet-I-H could be interfering with it. Figure 11 also allows us to affirm
there is no possible interference in the red fluorescence detection value, so we can deduce
that the whole signal detected in Figure 10 corresponds to mScarlet-I-H.
22
Figure 11. Excitation and emission spectra of two fluorescent molecules, integrated with the laser
characteristics of the flow cytometer. Spectra (Y axis) are shown as the percent of the maximum
excitation and emission fluorescence. The wavelength is portrayed in the X axis (in nanometers).
Excitation spectra are represented by the peak on the left, while emission spectra, by the peak on
the right. The numbers show the exact value of the peaks in nanometers. Seemingly, below the X
axis, the number on the left shows the flow cytometer’s channels’ excitation value (Ex), while the
one on the right shows the interval of emission values the detectors captured (Em) as a central
number followed by the half-length of the interval. The two fluorophores are: (A) mScarlet-I-H,
excitation (orange) and emission (red). Modified from (Song, Strack, Svensen, & Jaffrey, 2014). (B)
Spinach2–fluorophore (DFHBI), excitation (dotted line) and emission (solid line). Modified from
(Bindels et al., 2016).
Therefore, taking into account that the green fluorescence detection along constructs
(Figure 10) follows a highly similar trend to the one by the red fluorescence detection
(Figure 9), and that the fluorescence output of the former is significantly bigger, it is
concluded that the fluorescence emission of iSpinach-H has been either very low or null.
Since this phenomenon occurs along the four constructs, the lack of iSpinach-H and
DFHBI derived fluorescence could be explained by a general tendency for the backbone
of the construct to misfold and make the iSpinach-H sequence inaccessible to DFHBI.
This is consistent with our previous hypothesis.
The Csy4 catalytic activity can still be appreciated thanks to the fact that the values for
the mScarlet-I-H fluorescence of the induced samples vary greatly among constructs.
Nevertheless, there is one unexplained difference in trend between Figure 9 and Figure
10, which lies within the uninduced M0 and M1 constructs. While in Figure 9, their red
fluorescence was almost null (which led us to think an assembly error could be the cause),
23
in Figure 10, their values of green fluorescence are constant and uniform to the rest of
the uninduced construct population
Therefore, this could be an indicator that, even if very small quantities, there was some
green fluorescence coming from the iSpinach-H-DFHBI complex. This effect was more
clearly shown in the M0 and M1 uninduced constructs, so it could indicate that having no
Csy4 motifs, or having one in position number 1, allows for a better folding.
This improved folding, however, can only be noticed among the uninduced samples. This
leads us to believe that when the amount of RNA origami expressed increases, the chances
of misfolding and aggregation does as well.
Taking everything into account, the following hypothesis were stated. First, it is believed
that the constructs achieve a similar misfolded state. Second, the binding affinity of each
motif to Csy4 is the same: it is the spatial arrangement of the RNA origami that affects
Csy4 binding and cleavage. Third, this means that in the misfolded state, the locations of
the motifs from M3 and M2 are exposed and accessible to the Csy4, while the one for M1
remains inaccessible. Fourth, the exposed motifs are cleaved, and the RNA origami
degraded, avoiding accumulation of aggregates, reducing cell burden and allowing
mScarlet-I-H expression to be adequate.
Now we will look at the cleaving mechanism of Csy4, and test if our hypothesis is
consistent. Csy4 only cleaves the RNA in one spot (Figure 12), therefore the cleaved
motifs will remain bound to the scaffold.
Figure 12. Csy4 cleaves within pre-crRNA repeat sequences (black) to generate mature crRNAs
that contain a spacer sequence (colored line) flanked by fragments of the repeat. The substrate
sequence and cleavage site (red triangle) are indicated above. Extracted from (Sternberg et al.,
2012).
What is more, Csy4 lacks the ability to engage in multiple-turnover catalysis, since it
remains bound to the product. Sternberg et al. confirmed this by showing that the overall
yield of the cleavage reaction remained directly proportional to the Csy4 concentration
when present in sub-stoichiometric amounts relative to the substrate, even with incubation
times 200-fold longer than the reaction time constant.
Even if the Csy4 remains bound, the cleavage allows endonucleases to start degrading the
RNA origami, therefore our hypothesis is still consistent. In order to test it, as well as our
initial hypothesis, the experiment design should be improved and repeated.
24
With this aim, two new objectives are set for the new experiment: allowing the correct
folding of the RNA origami and improving the cleaving conditions for the Csy4.
Csy4 optimal cleaving conditions
A high improvement in the Csy4 cleaving will eliminate the variation that could stem
from partial cleaving, and make it so the differences observed in iSpinach-H fluorescence
be mainly due to the spatial location of the motifs.
Sternberg et al. performed some experiments to determine which is the most optimal
substrate-enzyme ratio for Csy4. It was shown to be the 2:1 ratio, while the 1:1 ratio leads
to approximately half of the RNA substrate being cleaved. Sternberg et al. were surprised
by this fact, and stated it could be due to partial specific activity of the purified enzyme.
With regards to our project, it is hypothesized that choosing a 1:1 ratio has also decreased
binding efficiency and cleavage, so a 2:1 would be more likely to show the differences
between constructs.
RNA origami design
Another factor to improve is the RNA origami design. This should prevent any misfolding
from occurring, so the iSpinach-H will be exposed and able to bind DFHBI. Two steps
are proposed:
1. Remove the iSpinach-H aptamer from the original position.
2. Add several iSpinach-H aptamers close to the Csy4 cleaving motifs.
In our base design, the iSpinach-H aptamer is thought to play a destabilizing role in that
position, and base on our conclusion, it also ends up being inaccessible to its fluorophore.
Therefore, it is suggested that a new design is made.
This design should be based on a bigger RNA origami scaffold, where it is possible to
locate Csy4 cleaving motifs in all four corners, and an iSpinach-H aptamer next to two of
them. A design based again on the 2H-AE tile is shown in Figure 13, mainly for
explanatory purposes.
From the experiment it was concluded that M3 and M2 (positions number 2 and 3,
respectively) showed the best cleaving efficiency. Therefore, the new iSpinach-H
sequences will find their location there.
Figure 13. 2D blueprint of the new RNA origami tile designs. The four corners for Csy4 motif
insertion are numbered from 1 to 4 (white numbers). The design contains the Csy4 motifs (yellow)
inserted simultaneously in the four possible corners, and an iSpinach-H aptamer sequence (pink)
next to two of them.
25
From the base design Figure 13 provides, the six different constructs can be inferred.
They will all will have the iSpinach-H sequences, but the Csy4 motifs will vary:
•
•
•
•
•
•
N0, no Csy4 motifs.
N1, Csy4 motif on corner position number 1 (see Figure 13).
N2, Csy4 motif on corner position number 2.
N3, Csy4 motif on corner position number 3.
N4, Csy4 motif on corner position number 4.
N5, Csy4 motifs on the four corners.
N0 will act as a control for maximum fluorescence and correct folding, given it has no
cleaving sites. N5 will act as a minimum fluorescence control, given it has all the possible
cutting sites. For this former construct, the amount of Csy4 co-expressed will have to be
increased, due to the already mentioned inability of Csy4 to perform multiple-turnover
catalysis.
In N2 and N3, the iSpinach-H aptamer close to them will be a clear indicator of the
cleaving effects, while the other iSpinach-H will provide a control-like function, given it
is shared among all the constructs. The fluorescence of the first is expected to decrease,
while the fluorescence of the former should be maintained.
In N1 and N4, the effects of RNA origami degradation after Csy4 cleavage will be tested.
Our hypothesis is that the cleavage in these constructs will not directly affect iSpinach
fluorescence, but this will decrease with time as the origami is degraded.
Applications
The building of a programmable switch that can lead to cell death has multiple
applications in the area of the biosciences. In fact, employing it as a kill-switch is just one
of the many possibilities.
To start with, assembled multidimensional RNA structures have been used as scaffolds
for the spatial organization of bacterial metabolism (Delebecque, Lindner, Silver, &
Aldaye, 2011). Delebecque et al. assembled engineered RNA modules into onedimensional and two-dimensional scaffolds with different protein-docking sites and used
them to control the spatial organization of a hydrogen-producing pathway. Thus,
rationally designed RNA assemblies can be used to construct functional architectures in
vivo.
With this approach, not only spatial, but also time (sequential) control would be a
possibility. This could be achieved by incorporating aptamers, ribozymes or mRNA
between the Csy4 cutting motifs in the RNA origami. These motifs, depending on their
affinity, will be sequentially cut and liberated by the Csy4 enzyme. As the Csy4
concentration increases, the cleavage of the motifs with the smaller binding affinity will
be a more likely event. Sequence order could also be controlled by employing different
RNA cutting endonucleases (in sequence) with their respective motifs, or alternatively,
by modifying the Csy4 and generating variants with significantly different binding motifs.
Being able to control the sequential liberation of functional RNA constructs has several
potential applications:
26
•
•
•
•
•
•
Metabolic engineering of enzymatic routes. The RNA origami could contain the
mRNAs to codify for different enzymes, or for sequences that perform stranddisplacement in their target mRNA and allow/repress translation. Therefore, the
expression of the enzymes that take part in a metabolic pathway could be regulated
and coordinated. It would then be possible to express synthetic enzymes that pose
a burden to the cells, and reduce their negative effects by controlling their window
of expression.
Building logical gates and circuits. In a RNA origami, the output of one step can
be the input of the next one, but to allow for a more precise sequential control, the
following mechanism can be implemented: imagine there are three sequential
outputs/steps that need to happen in a specific order, being the first one the
cleavage by Csy4. In second step, a ribozyme that cleaves the Csy4 binding motifs
is released as a secondary output. This will prevent Csy4 from cleaving the
residual motifs (thus restarting the 1st step) when the 3rd step is taking place.
What is more, the RNA origami could self-regulate its expression via a feedback
loop, such as the negative feedback loop proposed in this project.
Providing a multicomponent ordered response to an input. All the different
liberated outputs could be independent inputs that altogether lead the cell to
trigger a complex process. An example could be apoptosis, and the fact that
sequential logic gates can be possible inside the RNA allow for the potential
design of a kill-switch with a timer.
Simultaneously making use of the different functions RNA sequences can
perform: cleaving, binding, sequestering, strand-displacement.
Provide a safer approach than using DNA in the nucleus.
Viable in the cytoplasm.
Taking everything into account, the RNA origami would be similar to a microchip that
has a program encoded in it. It can be directly expressed inside the cells and can use
cellular components as inputs.
There is a rising need to finding ways to prevent genetically modified bacteria from
spreading into the wider environment, where they might grow and cause harm.
The kill-switch approach proposes modifying the cells so that in order to survive, they
will need to be a provided by a compound that cannot be synthesized or found in nature.
Another option would be to incorporate logical gates into the organisms, such as sets of
modular transcription factors that contain separate domains for sensing small molecules
(the inputs) and for, in accordance, regulating gene expression.
Therefore, the small molecule inputs are linked to the control of a specific promoter for
gene expression. If the right inputs are not present, a toxin will be expressed and the cell
will die (Chan, Lee, Cameron, Bashor, & Collins, 2016). This could also find an
application in intellectual property protection, as unauthorized growth of strains without
the appropriate passcode molecules would induce cell death (Chan et al., 2016).
A timer could be included in a kill-switch. This would be done by inserting sequential
steps of a certain time length between the input and the output, being the former the
apoptosis signal.
27
4.2 Negative feedback loop
We were unable to obtain results of our own, therefore we will discuss our hypothesis
and integrate it with the existing bibliography.
Csy4 binding mechanism
Regarding the stem-loop recognized by Csy4, a longer stem decreases binding to Csy4,
which means that one should add single-stranded regions with bulges (Sternberg et al.,
2012). However, this is not a necessarily negative feature when building a negative loop,
since different binding affinities will lead to different behaviors of the loop.
Our aim with the experiment was to characterize the different negative feedback loop
models in vivo. Our hypothesis was based on Sternberg et al.’s results for the binding
affinities of the different Csy4 motifs (Figure 14), and stated that, since the binding
affinity varies across motifs, the self-regulating effect dCsy4 causes would vary
accordingly.
Figure 14. Binding data and cleavage site mapping for base-pair insertion constructs. RNA
substrates containing base-pair insertions below the terminal C–G base pair were generated (left),
and electrophoretic mobility shift assays were performed with Csy4-H29A (right). Binding defects
were mildest for one or two A–U base-pair insertions (~1- and ~10-fold) and increased to ~200and ~800-fold for one or two G–C base pairs, respectively. The cleavage site for each RNA
substrate is indicated with a red triangle. Extracted from (Sternberg et al., 2012).
Sternberg et al. also concluded that Csy4 recognizes a crRNA repeat containing either a
GUAUA or a GUGUA loop. This is expected because both are likely to adopt GNR(N)A
penta-loop folds. GNRA is a tetranucleotide sequence usually found capping hairpin
stems (N is any base and R is a purine) (Dascenzo, Leonarski, Vicens, & Auffinger, 2017).
GNRNA is its pentanucleotide sequence version.
Characterization of the negative feedback loop
The negative feedback loop is expected to oscillate: initially, the low levels of dCsy4 will
allow its own mRNA to undergo translation, then a point will arrive where the dCsy4 are
high enough to block its own translation. This is because the dCsy4 binds to its own
mRNA, making the RBS inaccessible for the ribosome. Then, dCsy4 levels will decrease
once more, allowing for more translation of dCsy4 and continuing the cycle. This is
28
expected to eventually achieve a balance in medium expression level, as in a damped
oscillation, shown in Figure 15.
Figure 15. Schematic representation of the damped oscillation mechanism caused by the negative
feedback loop that describes the variation of expression levels for dCsy4. The Y axis is a relative
and hypothetical measure of dCsy4 expression, while the X axis represents time. Initially, the levels
of dCsy4 are low, so its translation will be unblocked (1st maximum, see unblocked dCsy4 mRNA).
Then, as the dCsy4 concentration increases, it will block its own translation, leading to a decrease
in concentration (1st minimum, see dCsy4 bound to the stem-loop in its mRNA). When the dCsy4
levels are low enough, translation will restart and the oscillation will be repeated. However, it is
expected that eventually blocked and unblocked dCsy4 mRNAs will achieve an equilibrium, so the
oscillations will be smaller as time goes by (see coexisting blocked and unblocked dCsy4 mRNAs).
This oscillator mechanism can be altered by including a new element in the system: an
RNA origami with binding motifs to Csy4. The goal of this RNA origami is to compete
with the mRNA of the dCsy4. Thus, when the RNA origami is expressed, the dCsy4 will
be sequestered by it, so it won’t bind its own mRNA nor prevent its translation.
As the levels of RNA origami increase, the maximum dCsy4 levels will increase as well.
However, eventually the dCsy4 levels will be high enough to saturate the RNA origami,
and start binding to its own mRNA once more. This will lead to a stabilization in a high
level of dCsy4 expression (see Figure 16).
29
Figure 16. Schematic representation of the dCsy4 sequestering and stabilizing mechanism of the
RNA origami. The Y axis is a relative and hypothetical measure of dCsy4 expression, while the X
axis represents time. The RNA origami is represented by a trapezoid, with dCsy4 bound to it.
Initially, the levels of dCsy4 start growing, as the RNA origami will sequester the expressed dCsy4,
thus preventing its negative self-regulation. When the levels are high enough for dCsy4 to leak
(RNA origami are saturated) and block its own translation, an equilibrium will be achieved in the
dCsy4 expression.
Applications
A process that alternates between activation and inhibition allows for a finer control, in
this case, of enzymatic levels. In this negative feedback loop, the activated state is the
base one, and it is the dCsy4 that acts as the inhibiting mechanism.
Negative feedback oscillators exist in nature. Two examples are the circadian gene
expression in some cyanobacteria and the cyclic binding of cofactors to the estrogensensitive pS2 promoter. In the former one, a coordinated sequence of binding and
unbinding events modifies the DNA packing and nucleosome structure to enable
transcription to proceed (Pigolotti, Krishna, & Jensen, 2007).
In a broader sense, this autonomous and clock-like regulatory circuit promotes
repeatability and reduces variation. In synthetic biology, these are two important features
when designing logical circuits, and especially, when programming them to act in a
synchronic or cyclical fashion. Therefore, it could allow a new type of input to be used
when programming life: time.
Had the experiment resulted successful, the specific features and parameters of the
oscillator could have been analyzed by algorithms such as the one proposed by Pigolotti
et al. (Pigolotti et al., 2007). This algorithm investigates the oscillating pattern by dividing
the data set into intervals whose ends are determined by the occurrence of an extremal
value of a variable. In our case, the oscillating pattern is seen in the dCsy4 expression and
the external variable would be the amount of dCsy4 expressed.
30
5 Conclusion
Kill-switch
The fluorescence of mScarlet-I-H is directly proportional to its expression and therefore,
that of Csy4. These have both been affected by the incorrect folding of the RNA origami,
which leads to the formation of aggregates. These aggregates, when in high numbers,
promote the loss of fitness (reduced growth speed and protein production), which is why
the expression of Csy4 and mScarlet-I-H is shown to have diminished in some constructs
(M0 and M1).
All the constructs are thought to have misfolded, since none had the iSpinach aptamer
accessible to DFHBI. However, depending on the location of the Csy4 motif, some of
them remained accessible to Csy4, which cleaved them, promoting the degradation of the
RNA origami and preventing aggregation. Thus, these constructs (M3 and M2) rendered
highest mScarlet fluorescence.
For future experiments, the RNA tiles will be redesigned to allow the correct folding of
the RNA origami, as well as the accessibility of the functional motifs. What is more,
optimal cleavage conditions for Csy4 will be sought, by, for example, increasing the
substrate-enzyme ratio to 2:1.
All in all, rationally designed RNA assemblies can be used to construct functional
architectures in vivo. With this approach, not only spatial, but also time (sequential)
control would be a possibility. This could be achieved by incorporating aptamers,
ribozymes or mRNA between the Csy4 cutting motifs. Therefore, these RNA origamis
could form logical gates, allowing the triggering of complex cell processes, such as the
induction of apoptosis (kill-switch).
Negative feedback loop
Unfortunately, the experimental procedure didn’t render any viable results. The
experimental error that led to this is believed to be an incorrect Golden Gate assembly for
the multi-gene cassettes. Therefore, this assembly should be performed once more, and if
the desired result is not achieved, the design of the constructs should be questioned.
Once the experimental errors are corrected, the protocol will be run once more. The
expected result will be a negative feedback loop, which will behave as a damped oscillator.
The oscillating pattern would be the variation of dCsy4 expression with time, while the
external explanatory variable would be the free levels of dCsy4. This is because the dCsy4
binds to its own mRNA, near the RBS, thus preventing the ribosome from translating.
An extra factor that can set a difference between the dCsy4 expressed and free levels is
the expression of RNA origamis containing dCsy4 binding motifs. Without them, the
oscillator will eventually stabilize in medium dCsy4 expression levels. In their presence,
however, more dCsy4 will be able to be expressed before triggering the negative
regulation mechanism, thus achieving an equilibrium in higher levels of dCsy4 expression.
In conclusion, the designed clock-like and autonomous regulatory circuit is a valuable
element for synthetic biology. By making time a new input, not only could computational
operations in living systems be controlled by means of space, but also by time. This circuit
31
has the potential to change its oscillatory pattern (RNA origami), act in a synchronized
manner, be delayed or become cyclical.
6 References
Adan, A., Alizada, G., Kiraz, Y., Baran, Y., & Nalbant, A. (2017). Flow cytometry: basic
principles
and
applications.
Critical
Reviews
in
Biotechnology.
https://doi.org/10.3109/07388551.2015.1128876
Bindels, D. S., Haarbosch, L., Van Weeren, L., Postma, M., Wiese, K. E., Mastop, M.,
… Gadella, T. W. J. (2016). MScarlet: A bright monomeric red fluorescent protein
for cellular imaging. Nature Methods. https://doi.org/10.1038/nmeth.4074
Chan, C. T. Y., Lee, J. W., Cameron, D. E., Bashor, C. J., & Collins, J. J. (2016).
“Deadman” and “Passcode” microbial kill switches for bacterial containment.
Nature Chemical Biology. https://doi.org/10.1038/nchembio.1979
Chappell, J., Takahashi, M. K., & Lucks, J. B. (2015). Creating small transcription
activating RNAs. Nature Chemical Biology. https://doi.org/10.1038/nchembio.1737
Chen, J. L., & Greider, C. W. (2005). Functional analysis of the pseudoknot structure in
human telomerase RNA. Proceedings of the National Academy of Sciences of the
United States of America. https://doi.org/10.1073/pnas.0502259102
Chen, Y., & Varani, G. (2010). RNA Structure. In Encyclopedia of Life Sciences.
https://doi.org/10.1002/9780470015902.a0001339.pub2
Dascenzo, L., Leonarski, F., Vicens, Q., & Auffinger, P. (2017). Revisiting GNRA and
UNCG folds: U-turns versus Z-turns in RNA hairpin loops. RNA.
https://doi.org/10.1261/rna.059097.116
Delebecque, C. J., Lindner, A. B., Silver, P. A., & Aldaye, F. A. (2011). Organization of
intracellular reactions with rationally designed RNA assemblies. Science.
https://doi.org/10.1126/science.1206938
Dirks, R. M., Lin, M., Winfree, E., & Pierce, N. A. (2004). Paradigms for computational
nucleic acid design. Nucleic Acids Research. https://doi.org/10.1093/nar/gkh291
Geary, C., Rothemund, P. W. K., & Andersen, E. S. (2014). A single-stranded architecture
for
cotranscriptional
folding
of
RNA
nanostructures.
Science.
https://doi.org/10.1126/science.1253920
Geary, C. W., & Andersen, E. S. (2014). Design principles for single-stranded RNA
origami structures. Lecture Notes in Computer Science (Including Subseries Lecture
Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
https://doi.org/10.1007/978-3-319-11295-4_1
Isaacs, F. J., Dwyer, D. J., & Collins, J. J. (2006). RNA synthetic biology. Nature
Biotechnology. https://doi.org/10.1038/nbt1208
Jalali, M., Zaborowska, J., & Jalali, M. (2017). The Polymerase Chain Reaction: PCR,
qPCR, and RT-PCR. In Basic Science Methods for Clinical Researchers.
https://doi.org/10.1016/B978-0-12-803077-6.00001-1
Jones, C. P., & Ferré-D’Amaré, A. R. (2015). RNA quaternary structure and global
symmetry.
Trends
in
Biochemical
Sciences.
32
https://doi.org/10.1016/j.tibs.2015.02.004
Lorenz, R., Bernhart, S. H., Höner zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P.
F., & Hofacker, I. L. (2011). ViennaRNA Package 2.0. Algorithms for Molecular
Biology. https://doi.org/10.1186/1748-7188-6-26
Mallikaratchy, P. (2017). Evolution of complex target SELEX to identify aptamers
against
mammalian
cell-surface
antigens.
Molecules.
https://doi.org/10.3390/molecules22020215
Pigolotti, S., Krishna, S., & Jensen, M. H. (2007). Oscillation patterns in negative
feedback loops. Proceedings of the National Academy of Sciences of the United
States of America. https://doi.org/10.1073/pnas.0610759104
Rivas, E., & Eddy, S. R. (1999). A dynamic programming algorithm for RNA structure
prediction including pseudoknots. Journal of Molecular Biology.
https://doi.org/10.1006/jmbi.1998.2436
Rothemund, P. W. K. (2006). Folding DNA to create nanoscale shapes and patterns.
Nature. https://doi.org/10.1038/nature04586
Saito, H., & Inoue, T. (2009). Synthetic biology with RNA motifs. International Journal
of Biochemistry and Cell Biology. https://doi.org/10.1016/j.biocel.2008.08.017
Seeliger, J. C., Topp, S., Sogi, K. M., Previti, M. L., Gallivan, J. P., & Bertozzi, C. R.
(2012). A Riboswitch-Based inducible gene expression system for mycobacteria.
PLoS ONE. https://doi.org/10.1371/journal.pone.0029266
Soediono, B. (1989). Alberts - Molecular Biology Of The Cell 4th Ed. Journal of
Chemical Information and Modeling.
Song, W., Strack, R. L., Svensen, N., & Jaffrey, S. R. (2014). Plug-and-play fluorophores
extend the spectral properties of spinach. Journal of the American Chemical Society.
https://doi.org/10.1021/ja410819x
Sparvath, S. L., Geary, C. W., & Andersen, E. S. (2017). Computer-aided design of RNA
origami structures. In Methods in Molecular Biology. https://doi.org/10.1007/978-14939-6454-3_5
Sternberg, S. H., Haurwitz, R. E., & Doudna, J. A. (2012). Mechanism of substrate
selection by a highly specific CRISPR endoribonuclease. RNA.
https://doi.org/10.1261/rna.030882.111
Svoboda, P., & Di Cara, A. (2006). Hairpin RNA: A secondary structure of primary
importance. Cellular and Molecular Life Sciences. https://doi.org/10.1007/s00018005-5558-5
Weber, E., Engler, C., Gruetzner, R., Werner, S., & Marillonnet, S. (2011). A modular
cloning system for standardized assembly of multigene constructs. PLoS ONE.
https://doi.org/10.1371/journal.pone.0016765
Westhof, E., & Auffinger, P. (2000). RNA Tertiary Structure. In Encyclopedia of
Analytical Chemistry. https://doi.org/10.1002/9780470027318.a1428
Xayaphoummine, A., Bucher, T., & Isambert, H. (2005). Kinefold web server for
RNA/DNA folding path and structure prediction including pseudoknots and knots.
Nucleic Acids Research. https://doi.org/10.1093/nar/gki447
33
Zadeh, J. N., Steenberg, C. D., Bois, J. S., Wolfe, B. R., Pierce, M. B., Khan, A. R., …
Pierce, N. A. (2011). NUPACK: Analysis and design of nucleic acid systems.
Journal of Computational Chemistry. https://doi.org/10.1002/jcc.21596
7 Supplementary material
A
B
C
34
D
E
F
35
G
H
Figure S1. Flow-cytometry results, from left to right, cell count, singlet count, iSpinach-fluorescence
and mScarlet fluorescence. (A) M0 induced, (B) M0 uninduced, (C) M1 induced, (D) M1 uninduced,
(E) M2 induced, (F) M2 uninduced, (G) M3 induced and (H) M3 uninduced.
Figure S2. mScarlet-I-H fluorescence arbitrary values (A.U.) obtained in the flow cytometry. The
results for the four different tile designs, and for each colony are displayed. For each, the blue bar
on the left corresponds to the uninduced sample while the orange bar on the right corresponds to
the sample induced with IPTG.
36
Figure S3. iSpinach-H fluorescence arbitrary values (A.U.) obtained in the flow cytometry. The
results for the four different tile designs, and for each colony, are displayed. For each, the blue bar
on the left corresponds to the uninduced sample while the orange bar on the right corresponds to
the sample induced with IPTG.
37
38
39
40